DBMS > GreptimeDB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Trino

System Properties Comparison GreptimeDB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Trino

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Editorial information provided by DB-Engines

Name

Description

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Time Series DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

greptime.com

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

trino.io

Technical documentation

docs.greptime.com

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

trino.io/broadcast
trino.io/docs/current

Developer

Greptime Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Trino Software Foundation

Initial release

2022

2010

2014

2012

2020 rebranded from PrestoSQL

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

Erlang

Java

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

hosted

Linux
macOS

for devlopment

Data scheme

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All properties auto-indexed by default

depending on connected data-source

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP API
JDBC

RESTful HTTP/JSON API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C++
Erlang
Go
Java
JavaScript

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

Python

View functions (Map-Reduce) in JavaScript

JavaScript

yes, depending on connected data-source

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

depending on connected data-source

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Simple rights management via user accounts

Access rights for users can be defined per database

Access rights can be defined down to the item level

SQL standard access control

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.